analyses across three waves...goals examine incidence of problem gambling in massachusetts...

ANALYSES ACROSS THREE

WAVES

Rachel A. Volberg, PhD

September 12, 2019

Overview of Presentation

Defining key terms

Background

Study goals & current status

Key findings

Implications

Future directions

Type of Study

SEIGMA:REPEAT CROSS-SECTIONAL STUDY

Collecting data “snapshots” at designated points over a period of time

Not the same people in each snapshot

MAGIC:

LONGITUDINAL COHORT STUDY

Collecting a “moving picture” of data from a group of people at designated time points

Following the same people over a period of time

Epidemiological bathtubs

OR

Moved

Etiology

The study of causation,

or what causes a

particular condition

The study of how a

condition, in this case

problem gambling,

develops and

fluctuates over timeGambling Behavior

Protective Factors

Risk Factors

Genes

Problem Gambling

Background

Early small-scale cohort studies of gambling &

problem gambling all had serious limitations

These limitations led to launch of 5 large-scale

cohort studies in 4 countries

Comparing Large-scale Cohort Studies

Alberta, Canada

LLLP

Ontario, Canada

QLS

SwedenSwelogs

AustraliaVGS

New Zealand

NGS

Data collection period 2006-2011 2006-2011 2008-2014 2008-2012 2012-2015

Recruited sample 1,808 4,123 8,165 15,000 6,251

Assessment length 2-3 hour 1-2 hour 15-25 min 15-25 min 45 min

Interval (months) 17-221 12 122 12 12

PG Measure CPGI 5+ PPGM CPGI 5+ CPGI 8+ CPGI 8+

Baseline PG prevalence 3.6% 3.1% 1.0% 2.6% 2.5%

Wave 2 PG prevalence 2.0% 2.9% 1.1% 1.5% 2.0%

Incidence (Wave 1 – Wave 2) N/A 1.4% 0.8% 0.12% 0.28%

Proportion of Wave 2 PGs that are new cases

N/A 49.0% 73.5% 33.3% 51.6%

1 This is the median elapsed time between waves for all respondents. 2 Between Wave 1 and Wave 2; the interval between subsequent waves was 24 months.

Why MAGIC?

There have been no major cohort studies of

gambling in the US

Change in gambling availability in MA during this

study will be greater than for other cohort studies

conducted internationally

Addresses limitations & builds on findings of

previous studies

Synergistic with SEIGMA, producing results richer

than either study alone

Goals

Examine incidence of problem gambling in Massachusetts

Proportion of a population that newly develops a condition over a specified period of time

New cases vs. relapsing cases require different mix of services

Examine stability and transitions associated with problem gambling

Patterns of continuity and discontinuity among different risk groups

Develop an etiological model of problem gambling

Etiology – cause or causes of a disease or condition

Identifies risk & protective factors

Utility in guiding development of prevention, intervention, treatment, recovery support strategies

Current Status

Wave 1 = Baseline General Population Survey (BGPS) (n=9,578)

Stratified sample drawn based on risk profile (n=4,860)

Wave 2

Data collection launched March 2015, completed Sept 2015

Cohort established (n=3,139)

Wave 3

Expanded questionnaire to capture etiological factors more comprehensively

Data collection launched April 2016, completed August 2016 (n=2,450)

Wave 4

Expanded questionnaire includes additional etiological factors

Data collection launched March 2018, completed July 2018 (n=2,443)

Wave 5

Few changes to questionnaire

Data collection launched March 2019, completed July 2019 (n~2,300)

Wave 6

Few changes to questionnaire

Data collection to launch March 2020

Weighting

Weighted data used in calculating incidence to allow for more confident generalizing to MA adult population

Weighting not used in assessing changes in gambling behavior, stability and transitions, or etiology

Weighting accounts for stratified sample design and differential response rates by risk group

Weights include adjustments for gender, age, race/ethnicity, education

Additional weighting to adjust for likely participation bias

Establishing the Cohort

Group SampleDrawn from

BGPSAchieved

Cohort

Response Rate by Group

%

Problem Gambler 133 81 61.4

At-Risk Gambler 450 295 65.7

Spends $1,200+ annually 1,088 726 67.2

Gambles weekly 792 534 67.6

Military service Sept 2001 or later 49 37 78.7

All other BGPS participants 2,348 1,466 63.1

Total 4,860 3,139 65.1

Data Collection Modes

Multi-Mode Data Collection Approach for Wave 1 and Wave 2

Multi-Mode Data Collection Approach for Wave 3

Matching Participants Across Waves

Completion Across Waves

Wave 1 (2013-2014)

Wave 2 (March-Sept 2015)

Wave 3 (April-August 2016)

Frequency Percent

1=no 2=yes 1=no 21 0.67

1=no 2=yes 2=yes 22 0.70

2=yes 2=yes 1=no 668 21.3

2=yes 2=yes 2=yes 2428 77.3

Where the cohort comes from

Changes in Gambling Participation

0

10

20

30

40

50

60

70

80

90

100

All gambling All lottery Casino (OS) Sports Private Bingo Horse racing Online

Wave 1 Wave 2 Wave 3

Change in PG Status

Problem Gambling Status in Wave 1 and Wave 2

Wave 1 Wave 2 Frequency

Not a problem gambler Not a problem gambler 2,943

Not a problem gambler Problem gambler 60 3,003

Problem gambler Not a problem gambler 40

Problem gambler Problem gambler 39

3,082

Missing Not a problem gambler 45

Missing Problem gambler ---

Not a problem gambler Missing 8 3,139

Dash (---) indicates value suppressed due to small cell size

Problem Gambling Status in Wave 2 and Wave 3

Wave 2 Wave 3 Frequency

Not a problem gambler Not a problem gambler 2,330

Not a problem gambler Problem gambler 35

2,365

Problem gambler Not a problem gambler 38

Problem gambler Problem gambler 40

2,443

Missing Not a problem gambler ---

Not a problem gambler Missing ---

2,450

Missing Did not complete Wave 3 5

Not a problem gambler Did not complete Wave 3 659

Problem gambler Did not complete Wave 3 25

3,139 Dash (---) indicates value suppressed due to small cell size

PG Incidence and Remission

Incidence and Remission Rates, Wave 2 to Wave 3

Wave 2 to Wave 3

Problem Gambler UN1 N2

No No 2,330 5,054,316

No Yes 35 58,899

Incidence rate 1.5% 1.2%

Yes No 38 82,090

Yes Yes 40 104,496

Remission rate 48.7% 44.0% 1 Unweighted N refers to the total number of respondents who completed the PPGM 2 Weighted N is the total number of respondents who completed the PPGM weighted to the MA population

Incidence and Remission Rates, Wave 1 to Wave 2

Wave 1 to Wave 2

Problem Gambler UN1 N2

No No 2,943 5,032,690

No Yes 60 123,631

Incidence rate 2.0% 2.4%

Yes No 40 57,385

Yes Yes 39 58,764

Remission rate 50.6% 49.4% 1 Unweighted N refers to the total number of respondents who completed the PPGM 2 Weighted N is the total number of respondents who completed the PPGM weighted

to the MA population

Stability & Change Across 3 Waves

Recreational Gamblers

70.2% remained in this category across 3 waves

Non-Gamblers


Problem/Pathological Gamblers


At-Risk Gamblers


Stability & Change Across 3 Waves

Others moved in and out of risk categories across waves

Some individuals experienced decrease in risk category Problem → At-Risk At-Risk → Recreational Recreational → Non-Gambler

Some individuals experienced increase in risk category Non-Gambler → Recreational Recreational → At-Risk At-Risk → Problem Recreational → Problem

Some individuals were ‘in transition’ moving to lower or higher category at Wave 2 and then back at Wave 3

Wave 1 Wave 2 Wave 3 Frequency Percent % change in risk

classification from Wave 1

at risk gambler non gambler non gambler --- --- 54.4

at risk gambler non gambler recreational gambler --- ---

at risk gambler recreational gambler non gambler --- ---

at risk gambler recreational gambler recreational gambler 112 4.63

at risk gambler at risk gambler non gambler --- ---

at risk gambler at risk gambler recreational gambler 42 1.74

at risk gambler at risk gambler at risk gambler 63 2.61 20.4

at risk gambler recreational gambler at risk gambler 37 1.53 18.1

at risk gambler recreational gambler problem or pathological gambler --- ---

at risk gambler problem or pathological gambler

non gambler --- ---


recreational gambler 6 0.25


at risk gambler 10 0.41

at risk gambler at risk gambler problem or pathological gambler 9 0.37 7.1


problem or pathological gambler 13 0.54

309

problem or pathological gambler non gambler recreational gambler --- --- 48.5

problem or pathological gambler recreational gambler recreational gambler 7 0.29

problem or pathological gambler at risk gambler recreational gambler --- ---

problem or pathological gambler at risk gambler at risk gambler 10 0.41

problem or pathological gambler problem or pathological gambler

recreational gambler --- ---


at risk gambler 8 0.33


problem or pathological gambler 21 0.87 32.8

problem or pathological gambler recreational gambler at risk gambler --- --- 18.8

problem or pathological gambler recreational gambler problem or pathological gambler --- ---

problem or pathological gambler at risk gambler problem or pathological gambler 6 0.25

64

Transitions Between PPGM Groups Across Three Waves (unweighted)

Dash (---) indicates value suppressed due to small cell size

Risk Classification Legend: White = no change in risk Light blue = decrease in risk Dark blue = increase in riskBlack = in transition

Discussion

Small increases in gambling participation but Wave 2-3 changes appear to be due to changes in how questions were phrased

Notable that out-of-state casino gambling decreased significantly from Wave 2 to Wave 3

Suggests that slot parlor (which opened in June 2015) has been successful at ‘recapturing’ MA residents who previously gambled at out-of-state casinos

PG incidence Wave 1-2 (prior to casinos) was high (2.4%) but is subject to methodological limitations

Differential response rates may have resulted in over-enrollment of heavier gamblers

Longer inter-assessment interval (16.5 months vs. 12 months)

Reliability of PG measures based on self-report

PG incidence Wave 2-3 declined (1.2%) and remission was substantial (44%)

Number of individuals becoming PGs and number remitting within cohort were almost equal

Discussion

Stability and transition rates similar to cohort studies in other jurisdictions

One difference is larger proportion of MA cohort that transitioned over assessments

Victoria = 4.3% transitioned down, 5.6% transitioned up

MA = 13.0% transitioned down, 14.2% transitioned up, 13.2% moved at both Wave 2 and 3

Possible reasons for differences

May be due to how PG was measured in each study

May be due to longer inter-assessment period from Wave 1-2

MA cohort includes much higher proportion of individuals selected from high risk strata of BGPS

Discussion

Recent addiction research suggests that these disorders are more

unstable than historically thought

Chronic in the sense that there is a higher lifetime risk for relapse, continuation

Those experiencing addictions tend NOT to have unremitting manifestations

Evolving understanding of gambling addiction led to introduction of “past

12-month” timeframe for Disordered Gambling in DSM-5

Some people merit clinical attention even if they do not meet the more

stringent “unremitting” definition of addiction

DSM-5 recognizes mild, moderate, and severe levels of Disordered Gambling

Limitations

Not all sampling biases can be accounted for with weighting

Individuals recruited into cohort were aware that the study was about

gambling and decision to participate could have been shaped by this

knowledge

Repeated surveys known to influence self-report of behavior with

respondents seeking to convey some improvement to researchers

Observed changes over time are sensitive to the reliability of the

measurement instrument

Implications for Prevention & Treatment

Stable prevalence rate over time can be due to:

Ongoing unremitting PG in same individuals OR

Rate of new cases roughly equal to rate of remission

Two scenarios have different implications

If PG is chronic, new cases uncommon = preferable to devote

more resources to treatment rather than prevention

If incidence & recovery both high = greater emphasis on

prevention in addition to treatment, recovery support


Number of new PGs in Wave 2 (n=60) higher than ongoing

unremitting cases (n=39)

Number of new PGs in Wave 3 (n=35) lower than ongoing

unremitting cases (n=40)

Relatively high remission rate continued from Wave 2 to Wave 3

Suggests that both prevention and treatment resources may be

beneficial to further decrease incidence & accelerate remission in

Massachusetts


Stability & transitions in MA cohort suggest that PGs and At-

Risk Gamblers are unlikely to transition to Non-Gambler status

When Recreational Gamblers transition, they are also unlikely

to transition to Non-Gambler status

Consistent with research that ‘controlled’ gambling may not be

incompatible with recovery from PG

Treatment providers may want to consider offering moderate gambling

consumption as a treatment goal to increase likelihood of treatment-

seeking & treatment adherence

Eventual transition to abstinence may emerge from controlled

consumption

Future Directions

Goal of study is to uncover high-risk populations in MA

Inform development of effective and efficient prevention and

treatment programs in the Commonwealth

Next report will examine longitudinal predictors of PG across 4

waves

Focus on differences in incidence, transitions by gender, race/ethnicity,

income, region, severity of disorder

Examine involvement w/specific types of gambling

Examine predictors of remission inc. accessing treatment

Questions?

For more information, visit:

www.umass.edu/macohort

http://www.umass.edu/macohort

analyses across three waves...goals examine incidence of problem gambling in massachusetts...

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